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Updated: Jun 29, 2025
A Mouse Distraction Osteogenesis Model
Published on: November 14, 2018
Bone Volume Analysis and Associated Influencing Factors in Mandibular Distraction Osteogenesis: A Retrospective
Peijie Tan1, Wael Telha1, Ruiye Bi2
1Resident, State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Oral & Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Background:
Distraction osteogenesis is a progressively popular technique for maxillofacial bone reconstruction, but there is a notable gap in the analysis of bone volume within the distraction segment and the exploration of associated influencing factors.
Purpose:
The purpose of this study was to quantitatively analyze the new bone volume and the distraction gap volume in the three-dimensional (3D) model and explore the influencing factors associated with the percentage of the new bone volume to the distraction gap volume.
Study Design, Setting, Sample:
This retrospective study included patients who underwent maxillofacial distraction osteogenesis treatment at the West China Hospital of Stomatology between 2014 and 2022, utilizing the mandibular distractor (Cebei, Ningbo, China). Exclusion criteria encompassed individuals with incomplete clinical or radiographical records as well as those who loss to follow-up.
Predictor Variable:
The predictor variables were age, sex, diagnosis, consolidation period duration, distraction modality, osteotomy area, distraction gap volume, and proximal bone segment volume.
Main Outcome Variable(S):
The outcome variable was osteogenic effect which defined as the percentage of the new bone volume to the distraction gap volume in the 3D model.
Covariates:
Not applicable.
Analyses:
T-tests were used to describe categorical variables, and Pearson correlation analysis was used to describe continuous variables. Linear regression was employed to assess the predictiveness of variables for osteogenic effect. Data are described as mean ± standard deviation; statistical significance was established at a P value < .05.
Results:
The study sample contained 35 patients(11 males and 24 females) with a mean age of 21.17 ± 11.82 years (range: 5 to 47 years) were included. The mean osteogenic effect of all samples was 78.89 ± 24.70%. Multiple linear regression models confirmed that the osteogenic effect was significantly influenced by the distraction gap volume (P = .003), proximal bone segment volume (P = .009), osteotomy area (P = .034), diagnosis (P = .004), and distraction modality (P = .021).
Conclusion And Relevance:
The percentage of new bone mass to simulated volume based on 3D model measurement can serve as an effective quantitative indicator for evaluating the osteogenic effect; our study demonstrates that distraction gap volume, proximal bone segment volume, osteotomy area, diagnosis, and distraction modality can statistically significantly influence the osteogenic effect.
